Flavopiridol Synergizes with Sorafenib to Induce Cytotoxicity and Potentiate Antitumorigenic Activity in EGFR/HER-2 and Mutant RAS/RAF Breast Cancer Model Systems
Bibliographic record
Abstract
Oncogenic receptor tyrosine kinase (RTK) signaling through the Ras-Raf-Mek-Erk (Ras-MAPK) pathway is implicated in a wide array of carcinomas, including those of the breast. The cyclin-dependent kinases (CDKs) are implicated in regulating proliferative and survival signaling downstream of this pathway. Here, we show that CDK inhibitors exhibit an order of magnitude greater cytotoxic potency than a suite of inhibitors targeting RTK and Ras-MAPK signaling in cell lines representative of clinically recognized breast cancer (BC) subtypes. Drug combination studies show that the pan-CDK inhibitor, flavopiridol (FPD), synergistically potentiated cytotoxicity induced by the Raf inhibitor, sorafenib (SFN). This synergy was most pronounced at sub-EC50 SFN concentrations in MDA-MB-231 (KRAS-G13D and BRAF-G464V mutations), MDA-MB-468 [epidermal growth factor receptor (EGFR) overexpression], and SKBR3 [ErbB2/EGFR2 (HER-2) overexpression] cells but not in hormone-dependent MCF-7 and T47D cells. Potentiation of SFN cytotoxicity by FPD correlated with enhanced apoptosis, suppression of retinoblastoma (Rb) signaling, and reduced Mcl-1 expression. SFN and FPD were also tested in an MDA-MB-231 mammary fat pad engraftment model of tumorigenesis. Mice treated with both drugs exhibited reduced primary tumor growth rates and metastatic tumor load in the lungs compared to treatment with either drug alone, and this correlated with greater reductions in Rb signaling and Mcl-1 expression in resected tumors. These findings support the development of CDK and Raf co-targeting strategies in EGFR/HER-2-overexpressing or RAS/RAF mutant BCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".